machine1 <- read_csv("data/index_1.csv") %>%
mutate(machine_id = "machine1")
sales <- machine1 |>
mutate(date = as_date(date),
datetime = as_datetime(datetime),
coffee_name=toupper(coffee_name))
skim(sales)| Name | sales |
| Number of rows | 3636 |
| Number of columns | 7 |
| _______________________ | |
| Column type frequency: | |
| character | 4 |
| Date | 1 |
| numeric | 1 |
| POSIXct | 1 |
| ________________________ | |
| Group variables | None |
Variable type: character
| skim_variable | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
|---|---|---|---|---|---|---|---|
| cash_type | 0 | 1.00 | 4 | 4 | 0 | 2 | 0 |
| card | 89 | 0.98 | 19 | 19 | 0 | 1316 | 0 |
| coffee_name | 0 | 1.00 | 5 | 19 | 0 | 8 | 0 |
| machine_id | 0 | 1.00 | 8 | 8 | 0 | 1 | 0 |
Variable type: Date
| skim_variable | n_missing | complete_rate | min | max | median | n_unique |
|---|---|---|---|---|---|---|
| date | 0 | 1 | 2024-03-01 | 2025-03-23 | 2024-10-06 | 381 |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| money | 0 | 1 | 31.75 | 4.92 | 18.12 | 27.92 | 32.82 | 35.76 | 40 | ▁▃▅▃▇ |
Variable type: POSIXct
| skim_variable | n_missing | complete_rate | min | max | median | n_unique |
|---|---|---|---|---|---|---|
| datetime | 0 | 1 | 2024-03-01 10:15:50 | 2025-03-23 18:11:38 | 2024-10-07 02:55:12 | 3636 |
unique(machine1$coffee_name)[1] "Latte" "Hot Chocolate" "Americano"
[4] "Americano with Milk" "Cocoa" "Cortado"
[7] "Espresso" "Cappuccino"